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- January 2010 (Revised March 2013)
- Case
HubSpot: Lower Churn through Greater CHI
By: F. Asis Martinez Jerez, Thomas Steenburgh, Jill Avery and Lisa Brem
HubSpot, a web marketing startup is under pressure from VCs to rapidly acquire new customers and to maintain a low level of customer churn. In the case, students explore the drivers of customer churn and uncover opportunities to increase customer retention across the...
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Keywords:
Business Startups;
Customer Relationship Management;
Customer Satisfaction;
Customer Value and Value Chain;
Forecasting and Prediction;
Consumer Behavior;
Happiness;
Consulting Industry
Martinez Jerez, F. Asis, Thomas Steenburgh, Jill Avery, and Lisa Brem. "HubSpot: Lower Churn through Greater CHI." Harvard Business School Case 110-052, January 2010. (Revised March 2013.)
- May 2006
- Article
Detection Defection: Measuring and Understanding the Predictive Accuracy of Customer Churn Models
By: Scott Neslin, Sunil Gupta, Wagner Kamakura, Junxiang Lu and Charlotte Mason
Neslin, Scott, Sunil Gupta, Wagner Kamakura, Junxiang Lu, and Charlotte Mason. "Detection Defection: Measuring and Understanding the Predictive Accuracy of Customer Churn Models." Journal of Marketing Research (JMR) 43, no. 2 (May 2006): 204–211.
- Forthcoming
- Article
Canary Categories
By: Eric Anderson, Chaoqun Chen, Ayelet Israeli and Duncan Simester
Past customer spending in a category is generally a positive signal of future customer spending. We show that there exist “canary categories” for which the reverse is true. Purchases in these categories are a signal that customers are less likely to return to that...
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Keywords:
Churn;
Churn Management;
Churn/retention;
Assortment Planning;
Retail;
Retailing;
Retailing Industry;
Preference Heterogeneity;
Assortment Optimization;
Customers;
Retention;
Consumer Behavior;
Forecasting and Prediction;
Retail Industry
Anderson, Eric, Chaoqun Chen, Ayelet Israeli, and Duncan Simester. "Canary Categories." Journal of Marketing Research (JMR) (forthcoming). (Pre-published online November 29, 2023.)
- Forthcoming
- Article
Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals
By: Ta-Wei Huang and Eva Ascarza
Firms are increasingly interested in developing targeted interventions for customers with the best response,
which requires identifying differences in customer sensitivity, typically through the conditional average treatment
effect (CATE) estimation. In theory, to...
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Keywords:
Long-run Targeting;
Heterogeneous Treatment Effect;
Statistical Surrogacy;
Customer Churn;
Field Experiments;
Consumer Behavior;
Customer Focus and Relationships;
AI and Machine Learning;
Marketing Strategy
Huang, Ta-Wei, and Eva Ascarza. "Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals." Marketing Science (forthcoming). (Pre-published online March 6, 2024.)
- Research Summary
Overview
By: Eva Ascarza
Professor Ascarza’s research primarily focuses on providing researchers and marketers a better understanding of how to manage customer retention so as to reduce churn and increase firm’s profitability. She addresses these issues by building empirical models of customer...
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